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Approaches for Clinical Supply Modelling and Simulation

  • Nitin R. PatelEmail author
  • Suresh Ankolekar
  • Pralay Senchaudhuri
Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

Clinical supply is impacted by decisions and events at every stage of a clinical trial. Protocol design, logistics planning, and operational dynamics pose challenges to the management of clinical supply in terms of complexity and uncertainty. In this chapter, we propose a simulation modelling approach to address these issues and support decision-makers in effectively managing clinical supply. The approach is comprehensively described in terms of underlying structure and process, and is illustrated with adaptive trials involving dropping of arms and a Bayesian responsive-adaptive design for dose finding.

Keywords

Adaptive clinical trials Clinical supply Simulation modelling Bayesian response-adaptive design 

References

  1. Abdelkafi C, Beck B, David B, Druck C, Horoho M (2009) Balancing risk and costs to optimize the clinical supply chain – a step beyond simulation. J Pharm Innov. doi: 10.1007/s12247-009-9063-5 Google Scholar
  2. Anisimov V, Fedorov V (2007) Modelling, prediction and adaptive adjustment of recruitment in multicentre trials. Stat Med 26:4958–4975Google Scholar
  3. Burnham N. Quinlan J, He W, Marshall M, Nichols N, Patel N, Parke T, Wong LB (2014) Effective drug supply for adaptive clinical trials: Recommendations by the DIA adaptive design scientific working group drug supply subteam, Therapeutic Innovation & Regulatory Science, published online 22 May 2014, doi: 10.1177/2168479014530968
  4. Byrom B (2002) Managing the medication supply chain using interactive voice response systems. Life Sci Today 3:16–18Google Scholar
  5. Dowlman N, Kwak M, Wood R, Nicholls G (2006) Managing the drug supply chain with e-processes. Appl Clin Trials 15(7):40–45Google Scholar
  6. McEntegart D (2003) Forced randomization: When using interactive voice response systems. Appl Clin Trials 12(10):50–58Google Scholar
  7. McEntegart D, O’Gorman B (2005) The impact on supply logistics of different randomization and medication management strategies using interactive voice response systems. Pharm Eng 25(5):36–46Google Scholar
  8. Nicholls G, Patel N, Byrom B (2009) Simulation: A critical tool in adaptive clinical trials. Appl Clin Trials 18(6):76–82Google Scholar
  9. Orloff J, Douglas F, Pinheiro J, Levinson S, Branson M, Chaturvedi P, Ette E, Gallo P, Hisrsch G, Mehta C, Patel N, Sabir S, Springs S, Stanski D, Evers M, Fleming E, Singh N, Tramontin T, Golub H (2009) The future of drug development: advancing clinical trial design. Nat Rev Drug Discov 8(12):949–957 doi: 10.1038/nrd3025
  10. Peterson M, Byrom B, Dowlman N, McEntegart D (2004) Optimizing clinical trial supply requirements: simulation of computer-controlled supply chain management. J Soc Clin Trials 1(4):399–412CrossRefGoogle Scholar
  11. Shang K (2011) Simple heuristics for optimal inventory policies in supply chains. Chapter 7 in Tutorials in Operations Research, INFORMS, pp 106–127, doi: 10.1287/educ.1110.0086
  12. Waters S, Dowlman I, Drake K, Gamble L, Lang M, McEntegart D (2010) Enhancing control of the medication supply chain in clinical trials managed by interactive voice response systems. Drug Inf J 44(6):727–740Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Nitin R. Patel
    • 1
    Email author
  • Suresh Ankolekar
    • 2
  • Pralay Senchaudhuri
    • 1
  1. 1.Cytel Inc.CambridgeUSA
  2. 2.Maastricht School of ManagementMaastrichtThe Netherlands

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